A growing number of pilot trials, such as TrialNet (http://www.niddk.nih.gov/welcome/releases/06-05-04.htm), are now being carried out nationwide and worldwide in an effort to find the cure for Type 1 diabetes (T1DM). All of these trials are based on the understanding that only 50% of "high risk" first-degree relatives of T1DM probands enrolled in these trials develop insulin requirement at 5 year follow-up. Endless discussions have taken place on how to develop new strategies to enhance sensitivity of multiple markers and in turn effectively enroll first-degree relatives into such trials prior to T1 DM onset. As of today, based on conventional autoantibody markers alone, the number of these relatives nationwide would be insufficient to complete all the proposed clinical trials. In the Preliminary Studies we demonstrate our expertise in applying a proteomic-based technology to identify pancreatic islet proteins reactive with antibodies in the sera of islet cell antibody (ICA) positive T1 DM patients but not in the sera of controls. To date, we have identified 9 candidate proteins by proteomic technology deemed worthy of investigation as new candidate autoantigens in T1DM. Our data also provide indirect evidence for the presence of an important subset of ICA that likely reacts with unidentified islet autoantigens. These data suggest that a novel subset of ICA is present in GAD65/IA-2 AA negative newly diagnosed T1DM patients and that a subset of ICA might also be related with rapid progression to insulin-requiring diabetes. A further characterization of this ICA response should facilitate a rational approach to ultimately discover a novel biochemical islet autoantibody marker(s) associated with rapid progression to T1DM. This objective will be initially exploited using proteomic-based technology (Specific Aim I) and this approach will subsequently be coupled with our longstanding expertise in developing biochemical islet autoantibody assays (Specific Aims II, III). Novel surrogate markers that will be identified by this approach might ultimately aid in monitoring the response to therapy aimed at delaying or reversing the disease process.